update

src/interface.jl

@@ -197,7 +197,7 @@ function decisionMaker(a::T)::Dict{Symbol, Any} where {T<:agent}
   #   - plan: Based on the current situation, what would you do to complete the task? Be specific.
   #   - action (Must be aligned with your plan): Can be one of the following functions:
   #       1) CHATBOX[text], which you can use to talk with the user. "text" is in verbal English. 
-  #       2) WINESTOCK[query], which you can use to find info about wine in your inventory. "query" is a search term in verbal English.
+  #       2) CHECKINVENTORY[query], which you can use to find info about wine in your inventory. "query" is a search term in verbal English.
   #   - observation: result of the action.
 
   #   You should only respond in format as described below:
@@ -222,15 +222,12 @@ function decisionMaker(a::T)::Dict{Symbol, Any} where {T<:agent}
 
     You must follow the following DO guidelines:
     - If the user interrupts, prioritize the user then get back to the guidelines.
+    - Check your inventory before mentioning any specific wine.
     - Get to know how much the user willing to spend
     - Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
     - Get to know what occasion the user is buying wine for
     - Get to know what characteristics of wine the user is looking for e.g. tannin, sweetness, intensity, acidity
     - Get to know what food will be served with wine
-      
-    You must follow the following DON'T guidelines:
-    - Don't mention any specific wine until you've checked your inventory.
-    - Check your inventory before recommending any specific wine.
 
     You should then respond to the user with interleaving Thought, Plan, Action and Observation:
     - thought: 
@@ -238,7 +235,7 @@ function decisionMaker(a::T)::Dict{Symbol, Any} where {T<:agent}
     - plan: Based on the current situation, state a complete plan to complete the task. Be specific.
     - action_name (Must be aligned with your plan): Can be one of the following functions:
         1) CHATBOX[text], which you can use to talk with the user. "text" is in verbal English. 
-        2) WINESTOCK[query], which you can use to find info about wine in your inventory. "query" is a search term in verbal English.
+        2) CHECKINVENTORY[query], which you can use to find info about wine in your inventory. "query" is a search term in verbal English.
           Good query example: black car with a stereo, 200 mile range and an electric motor.
           Good query example: How many car brand are from Asia?
     - action_input: input to the action
@@ -280,7 +277,7 @@ function decisionMaker(a::T)::Dict{Symbol, Any} where {T<:agent}
                         ["thought", "plan", "action_name", "action_input", "observation"], 
                         rightmarker=":", symbolkey=true)
 
-      if responsedict[:action_name] ∉ ["CHATBOX", "WINESTOCK"]
+      if responsedict[:action_name] ∉ ["CHATBOX", "CHECKINVENTORY"]
         error("decisionMaker didn't use the given functions ", @__LINE__)
       end
 
@@ -493,9 +490,8 @@ function evaluator(config::T1, state::T2
   Analyze the trajectories of a solution to a question answering task. The trajectories are 
   labeled by environmental observations about the situation, thoughts that can reason about 
   the current situation and actions that can be three types:
-  1) winestock[query], which you can use to find wine in your inventory.
+  1) CHECKINVENTORY[query], which you can use to find wine in your inventory.
-  2) chatbox[text], which you can use to interact with the user.
+  2) CHATBOX[text], which you can use to interact with the user.
-  3) recommendbox[answer], which returns your wine recommendation to the user.
 
   Given a question and a trajectory, evaluate its correctness and provide your reasoning and
   analysis in detail. Focus on the latest thought, action, and observation. Incomplete trajectories 
@@ -1056,8 +1052,8 @@ function think(a::T) where {T<:agent}
   response =
     if actionname == "CHATBOX"
       (result=actioninput, errormsg=nothing, success=true)
-    elseif actionname == "WINESTOCK"
+    elseif actionname == "CHECKINVENTORY"
-      winestock(a, actioninput)
+      checkinventory(a, actioninput)
     else
       error("undefined LLM function. Requesting $actionname")
     end

src/llmfunction.jl

@@ -1,7 +1,7 @@
 module llmfunction
 
-export  virtualWineUserChatbox, jsoncorrection, winestock,
+export  virtualWineUserChatbox, jsoncorrection, checkinventory,
-        virtualWineUserRecommendbox, userChatbox, userRecommendbox
+        virtualWineUserRecommendbox, userChatbox, userRecommendbox, extractWineAttributes
 
 using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs
 using GeneralUtils, SQLLLM
@@ -352,7 +352,7 @@ end
 julia> using ChatAgent
 julia> agent = ChatAgent.agentReflex("Jene")
 julia> input = "{\"food\": \"pizza\", \"occasion\": \"anniversary\"}"
-julia> result = winestock(agent, input)
+julia> result = checkinventory(agent, input)
 "{"wine 1": {\"Winery\": \"Pichon Baron\", \"wine name\": \"Pauillac (Grand Cru Classé)\", \"grape variety\": \"Cabernet Sauvignon\", \"year\": 2010, \"price\": \"125 USD\", \"stock ID\": \"ar-17\"}, }"
 ```
 
@@ -362,7 +362,7 @@ julia> result = winestock(agent, input)
 
 # Signature
 """
-function winestock(a::T1, input::T2
+function checkinventory(a::T1, input::T2
   )::Union{Tuple{String, Number, Number, Bool}, Tuple{String, Nothing, Number, Bool}} where {T1<:agent, T2<:AbstractString}
 
   wineattributes = extractWineAttributes(a, input)

test/runtest.jl

@@ -62,6 +62,9 @@ function text2textInstructLLM(prompt::String)
   return response
 end
 
+
+
+
   # Instantiate an agent
   a = YiemAgent.sommelier(
     text2textInstructLLM,
@@ -70,22 +73,22 @@ end
     id="testingSessionID",  # agent instance id
   )
 
-function main()
+# function main()
-  userinput = "Hello, I would like a get a bottle of wine."
+#   userinput = "Hello, I would like a get a bottle of wine."
-  for i in 1:10
+#   for i in 1:10
-    response = YiemAgent.conversation(a, Dict(:text=> userinput))
+#     response = YiemAgent.conversation(a, Dict(:text=> userinput))
-    println("")
+#     println("")
-    println("--> assistant response: \n", response)
+#     println("--> assistant response: \n", response)
-    println("")
+#     println("")
-    println("--> user input:")
+#     println("--> user input:")
-    userinput = readline()
+#     userinput = readline()
-  end
+#   end
-end
+# end
 
-main()
+# main()
 
 # """
-# I'm having a graduation party this evening. So I think a bottle of wine would be nice.
+# I'm having a graduation party this evening. I have no budget limit.
 # I have no idea. The party will be formal. What type of wine people usually get for this occasion?
 # What about sparkling Rose?
 
@@ -116,7 +119,7 @@ main()
 
 
 
+input = "query=\"medium-bodied dry white wine\""
 
-
+result = YiemAgent.extractWineAttributes(a, input)
-